The Shapley value is the solution concept in cooperative game theory that is most used in both theoretical as practical settings. Unfortunately, computing the Shapley value is computationally intractable in general. This paper focuses on computing the Shapley value of (weighted) connectivity games. For these connectivity games, that are defined on an underlying (weighted) graph, computing the Shapley value is #P-hard, and thus (likely) intractable even for graphs with a moderate number of vertices. We present an algorithm that can efficiently compute the Shapley value if the underlying graph has bounded treewidth. Next, we apply our algorithm to several real-world (covert) networks. We show that our algorithm can compute exact Shapley values for these networks quickly, whereas in prior work these values could only be approximated using a heuristic method. Finally, it is shown that our algorithm can also compute the Shapley value time efficiently for several larger (artificial) benchmark graphs from the PACE 2018 challenge.
翻译:Shapley 值是合作游戏理论中的一种解决方案概念, 在理论和实用设置中都是最常用的。 不幸的是, 计算 Shapley 值在总体上是难以计算的。 本文侧重于计算( 加权) 连通性游戏的 Shapley 值。 对于这些连接性游戏, 在基础( 加权) 图形中定义, 计算 Shapley 值是 # P- hard, 因此( 可能) 即使是具有中等数量 的顶点的图形, 也非常难解 。 我们提出了一个算法, 如果底点图形将树枝捆绑在一起, 我们就可以有效地计算 Shapley 值。 接下来, 我们将我们的算法应用到几个真实世界( 隐蔽) 网络 。 我们显示我们的算法可以快速计算这些网络的 Shapley 值, 而在过去的工作中, 这些值只能用超量法来比较。 最后, 我们的算法还显示, 我们的算法也可以对几个更大的( 人造的) 2018 挑战 。